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| Section | Objectives |
|---|---|
| AI Agents and Prompt Engineering | - Agent behavior, instructions, and tool usage
|
| Agentic Automation Fundamentals and Solution Design | - Agentic automation concepts, use cases, and architecture
|
| Governance, Security, and Responsible AI | - Enterprise governance and risk management
|
| Agentic Orchestration with UiPath Maestro | - Process orchestration and workflow coordination
|
| Human Oversight and User Interaction | - Human-in-the-loop controls
|
| Agent Evaluation and Quality Assurance | - Evaluation strategies and test datasets
|
| Integration, Reliability, and Operations | - Enterprise integration and production readiness
|
| Context Grounding and Knowledge Retrieval | - Knowledge sources and retrieval configuration
|
>> UiPath-AAPv1 Deutsche Prüfungsfragen <<
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65. Frage
A team is designing an AI assistant and wants to make sure the model always follows company compliance rules, regardless of what individual users request.
What type of prompt should be used to enforce these rules consistently?
Antwort: A
Begründung:
Option D identifies the appropriate instruction layer for establishing persistent behavioral rules in an AI assistant.
The system prompt defines the agent's operating role, authorized responsibilities, behavioral constraints, permitted activities, and requirements for handling user requests.
These instructions provide an operating framework that should remain applicable as users introduce different tasks or conversational topics.
For example, a financial-services assistant may require restrictions on exposing customer records, approving transactions without authorization, or processing requests outside its assigned responsibilities.
Embedding these requirements in the system prompt provides the agent with higher-priority behavioral instructions than ordinary task-specific user input.
Options A and C incorrectly assign persistent compliance controls to user prompts. Option B concerns conversational tone rather than governance requirements.
However, system prompts alone cannot guarantee compliance. Language-model behavior remains probabilistic, and user-controlled inputs may contain attempts to redirect the agent.
UiPath provides additional safeguards, including AI Trust Layer governance policies, centralized guardrails, tool permissions, evaluations, and human-in-the-loop escalation.
A production-grade solution should therefore combine system-level instructions with enforceable technical controls, monitoring, and approval mechanisms for consequential operations.
Official UiPath references/topics: Agents - Best Practices for Building Agents; Automation Ops - AI Trust Layer Policies.
Technical qualification: System prompts alone cannot guarantee compliance.
66. Frage
What must be configured to create an Automation Ops policy for a specific tenant?
Antwort: B
Begründung:
Option C most closely matches the general policy-details configuration described in the official UiPath Automation Ops documentation.
Automation Ops provides centralized governance controls for supported UiPath products, including Studio, Integration Service, and AI Trust Layer capabilities.
When an administrator creates or edits a governance policy, the Policy Details section includes a policy name, priority, description, and an availability setting.
The policy name identifies the governance configuration and should be unique enough to distinguish it from other policies.
Priority determines precedence when multiple group-level policies apply to the same user. UiPath applies the policy with the lowest numerical priority value first.
Description provides supplementary information about the policy's purpose and intended application.
Option A incorrectly substitutes Roles for Description. Option B omits Priority. Option D incorrectly introduces Period in place of the documented Priority setting.
However, the original question is incomplete if interpreted as an exhaustive list of mandatory fields.
Current UiPath documentation also includes Availability (days), which determines how long a cached policy remains applicable when the governed product cannot connect to Automation Ops.
Furthermore, the description is optional, and creating a policy does not automatically apply it to a tenant. The policy must subsequently be deployed to the intended tenant.
Official UiPath references/topics: Automation Ops - Configure a Governance Policy; Deploy Governance Policies.
Technical qualification: C best matches principal policy details, but description is optional and Availability (days) is another configuration property.
67. Frage
When configuring evaluation sets to compare model/temperature combinations, which evaluator categories let you select the model used for evaluation?
Antwort: A
Begründung:
Option B correctly identifies the evaluator categories that expose a Model selection field in UiPath Agent evaluations.
UiPath separates evaluators into three principal categories: Deterministic, LLM-as-a-Judge, and Trajectory.
Deterministic evaluators use predefined comparison rules to evaluate outputs. Exact Match and JSON Similarity are examples. Because these evaluators do not require language-model inference to calculate their results, they do not include a Model selection field.
LLM-as-a-Judge evaluators use a language model to assess response characteristics such as semantic similarity, faithfulness, and contextual relevance. Their configuration allows developers to select the evaluation model.
Trajectory evaluators also use an LLM, but their purpose is to examine the agent's overall execution behavior, including intermediate actions, decisions, and tool usage.
Consequently, both LLM-as-a-Judge and Trajectory evaluators support model selection.
Option A incorrectly excludes LLM-as-a-Judge evaluators. Option C incorrectly assigns model selection to deterministic evaluators. Option D ignores the distinction between model-based and rule-based scoring.
Importantly, choosing an evaluator's model is different from choosing the model and temperature used to execute the agent. These are separate configuration concerns.
Official UiPath references/topics: Agents - Evaluations: Evaluator Categories and Defining Evaluators.
68. Frage
How is access to Context Grounding indexes controlled in UiPath Autopilot?
Antwort: B
Begründung:
Option B precisely matches UiPath's documented access-control requirements for Context Grounding indexes used by Autopilot for Everyone.
Context Grounding enables Autopilot to retrieve relevant information from indexed enterprise knowledge sources. Because those sources may contain confidential business information, access must respect established authorization boundaries.
UiPath manages index access through Orchestrator folder permissions.
Three conditions must be satisfied before a user can access a particular Context Grounding index through Autopilot for Everyone.
First, the index must exist in the appropriate Orchestrator folder. Second, the user must be assigned to that folder with suitable access permissions. Third, the index must be enabled in the Autopilot configuration.
Administrators enable indexes through Automation Cloud, under Admin, AI Trust Layer, and Autopilot for Everyone, using the Context Grounding configuration section.
During enablement, the administrator selects the relevant Orchestrator folder and index and supplies a description that helps Autopilot determine when the index should be queried.
Option A incorrectly requires independent administrator approval for every index access. Option C introduces an unsupported exclusive analyst role. Option D incorrectly assumes all tenant users receive identical access.
The documented folder-based model preserves logical separation between knowledge collections while allowing authorized users to retrieve relevant information.
Official UiPath references/topics: Autopilot - Context Grounding, Managing Access and Enabling Indexes.
69. Frage
Given the following BPMN for the "SME to review the discrepancies" task, which option should be selected in the "Action" dropdown?
Original exhibit - Question 56
Antwort: D
Begründung:
Option A identifies the documented implementation action for creating a human review task within a UiPath Maestro BPMN process.
The exhibit shows a User task named "SME to review the discrepancies" with an Action App selected in its properties panel.
In Maestro, a User task represents an activity requiring human participation rather than autonomous execution by an AI agent or robotic automation.
The Create action app task implementation integrates UiPath Action Apps and Action Center to provide a structured interface through which an assigned user can review business information and submit a decision.
In this scenario, the subject matter expert reviews discrepancies identified during invoice and purchase-order matching.
The Action App receives relevant process variables, presents the discrepancies, and collects the reviewer's decision.
The BPMN process can subsequently route execution through approval or rejection paths according to the submitted outcome.
Option B introduces a validation-specific action not represented by the standard task implementation shown.
Options C and D introduce alternative action names that do not match the documented selection for this task.
UiPath's official Maestro implementation examples use Create action app task for human approval and discrepancy-resolution activities.
The appropriate choice is therefore A.
Official UiPath references/topics: Maestro Orchestrate - Tasks; Implementing a Complex Process; Extracting and Validating Documents.
70. Frage
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